File size: 2,038 Bytes
8ede856 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | import json
from typing import Protocol, runtime_checkable
from ..message import Message, TextPart
@runtime_checkable
class TokenCounter(Protocol):
"""
Protocol for token counters.
Provides an interface for counting tokens in message lists.
"""
def count_tokens(
self, messages: list[Message], trusted_token_usage: int = 0
) -> int:
"""Count the total tokens in the message list.
Args:
messages: The message list.
trusted_token_usage: The total token usage that LLM API returned.
For some cases, this value is more accurate.
But some API does not return it, so the value defaults to 0.
Returns:
The total token count.
"""
...
class EstimateTokenCounter:
"""Estimate token counter implementation.
Provides a simple estimation of token count based on character types.
"""
def count_tokens(
self, messages: list[Message], trusted_token_usage: int = 0
) -> int:
if trusted_token_usage > 0:
return trusted_token_usage
total = 0
for msg in messages:
content = msg.content
if isinstance(content, str):
total += self._estimate_tokens(content)
elif isinstance(content, list):
# 处理多模态内容
for part in content:
if isinstance(part, TextPart):
total += self._estimate_tokens(part.text)
# 处理 Tool Calls
if msg.tool_calls:
for tc in msg.tool_calls:
tc_str = json.dumps(tc if isinstance(tc, dict) else tc.model_dump())
total += self._estimate_tokens(tc_str)
return total
def _estimate_tokens(self, text: str) -> int:
chinese_count = len([c for c in text if "\u4e00" <= c <= "\u9fff"])
other_count = len(text) - chinese_count
return int(chinese_count * 0.6 + other_count * 0.3)
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